Genentech has artfully identified a large gap in science--and claimed a leadership role. Maybe it is just me but what a great podcast. Full disclosure, I came from scientific inquiry as a bench scientist to a self-identified datapreneur or as a few clients like to joke -- "a data whisperer". I relate to the conversations introduced in the first 8 episodes of the podcast and I think you will too. The snippet about biomarkers and checkpoint inhibitors is a nice place to start.

Here is the problem. Quite often I sit in rooms with industry teams at a cross-roads. We discuss market access, positioning, medical education, clinical trial design and pharmacovigilance but rarely do we have the opportunity to level-set the conversation. We often assume that because we are all scientists--we know the "ins and outs" of the entire drug development process.

I get it. Science is complicated. I would argue more complicated than necessary. The journal PLOS ONE published an article, Life Science’s Average Publishable Unit (APU) Has Increased over the Past Two Decades. The authors explain how data bloat correlates to a journal's impact factor (ranging from 3.8 to 32.1). Engaging a metric, The APU, they are able to score the number of data items, density of composite figures, and numbers row authors, pages, and references to show the increase over the last few years.

"The increasing APU size over time is important when considering the value of research articles for life scientists and publishers, as well as, the implications of these increasing trends in the mechanisms and economics of scientific communication."

STAT published an article in 2016, Are Science Papers Becoming Too Complex although since the evolution of their STAT Plus subscription fire-wall I tend to seek out news elsewhere. Don't get me wrong--we all need to make a living but I find it a bit disingenuous when social media headlines tease the latest discussions, you click, and are turned away unless you shell out $29/month.

​There is an old adage attributed to Albert Einstein, "If you can't explain it simply, you don't understand it well enough." Listen to the podcast--they understand science.

Observations, not stories, are the pillars of good science. Today’s journals however, favor story-telling over observations, and congruency over complexity. As a consequence, there is a pressure to tell only good stories.

​Moreover, incentives associated with publishing in high-impact journals lead to loss of scientifically and ethically sound observations that do not fit the storyline, and in some unfortunate cases also to fraudulence. The resulting non-communication of data and irreproducibility not only delays scientific progress, but also negatively affects society as a whole.--ScienceMatters

I intentionally wrote this update in the context of cancer because the data deluge seems to have found a home. We need to look at immunotherapies, checkpoint inhibition, CAR-T data, personalized genomics in oncology, and the escalating costs of unproven therapies with an arched eyebrow. We have the data. Now let's start unpacking the information.

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Bonny is a data enthusiast applying curated analysis and visualization to persistent tensions between health policy, economics, and clinical research in oncology.